10 papers
Surface-based Molecular Design with Multi-modal Flow Matching
Fang Wu, Zhengyuan Zhou, Shuting Jin +3
Therapeutic peptides show promise in targeting previously undruggable binding sites, with recent advancements in deep generative models enabling full-atom peptide co-design for spe…
Uncalibrated Reasoning: GRPO Induces Overconfidence for Stochastic Outcomes
Michael Bereket, Jure Leskovec
Reinforcement learning (RL) has proven remarkably effective at improving the accuracy of language models in verifiable and deterministic domains like mathematics. Here, we examine…
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Xuan Zhang, Limei Wang, Jacob Helwig +60
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…
BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
Yusuf Roohani, Andrew Lee, Qian Huang +6
Agents based on large language models have shown great potential in accelerating scientific discovery by leveraging their rich background knowledge and reasoning capabilities. In t…
Learning production functions for supply chains with graph neural networks
Serina Chang, Zhiyin Lin, Benjamin Yan +8
The global economy relies on the flow of goods over supply chain networks, with nodes as firms and edges as transactions between firms. While we may observe these external transact…
TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
Juntong Shi, Minkai Xu, Harper Hua +3
Synthesizing high-quality tabular data is an important topic in many data science tasks, ranging from dataset augmentation to privacy protection. However, developing expressive gen…